Database Reference
In-Depth Information
10.1 Approaches to Data Warehouse Design
A wide variety of approaches have been proposed for designing data
warehouses. They differ in several aspects, such as whether they target data
warehouses or data marts, the various phases that make up the design process,
and the methods used for performing requirements specification and data
warehouse design. This section highlights some of the essential characteristics
of the current approaches according to these aspects.
A data warehouse includes data about an entire organization that help
users at high management levels to take strategic decisions. However, these
decisions may also be taken at lower organizational levels related to specific
business areas, in which case only a subset of the data contained in a data
warehouse is required. This subset is typically contained in a
data mart
(see
Sect.
3.4
), which has a similar structure to a data warehouse but is smaller
in size. Data marts can be physically collocated with the data warehouse or
they can have their own separate platform.
Like in operational databases (see Sect.
2.1
), there are two major methods
for the design of a data warehouse and its related data marts:
Top-down design:
The requirements of users at different organizational
levels are merged before the design process begins, and one schema for
the entire data warehouse is built. Then, separate data marts are tailored
according to the characteristics of each business area or process.
Bottom-up design:
A separate schema is built for each data mart, taking
into account the requirements of the decision-making users responsible for
the corresponding specific business area or process. Later, these schemas
are merged in a global schema for the entire data warehouse.
The choice between the top-down and the bottom-up approach depends on
many factors, such as the professional skills of the development team, the size
of the data warehouse, the users' motivation for having a data warehouse, and
the financial support, among other things. The development of an enterprise-
wide data warehouse using the top-down approach may be overwhelming for
many organizations in terms of cost and duration. It is also a challenging
activity for designers because of its size and complexity. On the other hand,
the smaller size of data marts allows the return of the investment to be
obtained in a shorter time period and facilitates the development processes.
Further, if the user motivation is low, the bottom-up approach may deliver
a data mart faster and at less cost, allowing users to quickly interact with
OLAP tools and create new reports; this may lead to an increase in users'
acceptance level and improve the motivation for having a data warehouse.
Nevertheless, the development of these data marts requires a global data
warehouse framework to be established so that the data marts are built
considering their future integration into a whole data warehouse. A lack of
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